Multivariate analysis for the assessment of factors affecting industrial competitiveness: The case of Greek food and beverage industries

Abstract

Principal component analysis is integrated with canonical analysis to examine aspects of the competitiveness of two di!erent sectors of the Greek manufacturing, i.e. the food and the beverage industries. Di!erent measures of labour productivity, vertical integration, technological innovation and size of the "rms which are considered as critical factors of industrial competitiveness are used in the application of the principal component analysis. Canonical analysis is then applied to correlate the variables of labour productivity with the other variables. In the case of the food and beverage integrated sector, the results of the principal component analysis pinpoint that there are two main principal components: (a) labour productivity and vertical integration, and (b) technological innovation and size. The "rst factor depicts the internal organizational, structural and production processes changes realized so that the competitiveness of the sector "rms improves, whereas the second factor re#ects the response of the sector to technological and growth trends. The two variables of labour productivity are a!ected by the degree of vertical integration and, at a lesser degree, by a common factor of the size of the "rm and the level of investment for technological innovation.Application of multicriteria methods and multivariate analysis are the two main techniques that have been widely adopted [1}6]. Using multicriteria analysis approaches, the multidimensional character of all organizations can be better re#ected. The rankings obtained by the simultaneous consideration of multiple ratios can give useful information regarding the examined set of measures. However, due to the complexity of the MCA and the subjective selection of weights, its application is not free from problems.Elaborate statistical models have been also developed to forecast the business future, particularly with respect to bankruptcy risk [7,8]. Moreover, multivariate models have been applied to determine industry and corporate performance [9}12]. The main di!erence between multicriteria and multivariate methods is related to the way the various weights are assigned to the relative performance measures. Thus, in a multicriteria method the weights are subjectively determined by the decision maker, whereas in a multivariate method weights are estimated rather objectively by the data set.In recent years, major changes have taken place in technology and production systems, in organizational structures and cultures and in business strategies so that the industrial companies face the new challenges of the international markets and continue to be competitive in an ever-changing economic environment. Consequently, industrial business performance can no longer be assessed or explained by the unique use of "nancial ratios which are based on conventional cost accounting and management reporting systems [13}15].The competitiveness of an industrial "rm or sector depends on products' and services' quality, on customer's satisfaction, on productivity and e!ectiveness...

A decision support methodology to enhance the competitiveness of the Turkish automotive industry

“…This model can be applied to support strategic decisions about technology selection, productivity management, or investment planning. Lipovatz et al (2000) consider labour productivity, vertical integration, technological innovation, and firm size to be critical factors for industrial competitiveness and apply multivariate analysis to assess these factors in the Greek food and beverage industries. They find that productivity evolution correlates primarily with organisational and structural changes and, to a lesser extent, with growth rate and technological innovations.…”

Customer‐focused performance and the dynamic model for competence building and leveraging

“…As a key indicator of customer‐focused performance, customer satisfaction has often been considered one of the important dimensions of business performance, no matter when competitiveness or performance is studied, strategically or operationally. Enhanced customer satisfaction, greater customer loyalty, increased sales and productivity, high new product success, effectiveness of internal processes, innovation and improvement activities and higher employee satisfaction and empowerment are all inter‐linked and will always lead to more sustainable competitive advantage (Meyers et al .,1999; Lipovatz et al ., 2000). As for other aspects of customer‐focused performance, Zeithaml (1996) report a study of the links between service quality and customer behavior, in which the overall findings offer strong support for the intuitive notion that improving service quality can increase favorable behavioral intentions and decrease unfavorable intentions, implying great potential for higher profit.…”

Competitiveness of Russian regional oil complexes

“…have been extensively developed in the works of many scholars with regard to modern socio-economic systems. In addition to the aforementioned literature, credit should given to many other scholars, such as Carpenter et al (1988), Krugman (1994), Nickell (1996), Nachum et al (2001), Beggs and Klemperer (1992), Lau (1982), Schmidt (1997), Goldberg and Knetter (1999); Kadiyali et al (2001), Lipovatz et al (2000), Blakely (2001), Ahn (2002), Przybyla and Roma (2005), Putsis and Dhar (1998); Cotterill et al (2000), Roberts and Samuelson (1988), Shankar and Bayus (1999), Peteraf (1993), Aiginker (1998), Brooksbank and Pickernel (1999), Camagni (2002), Clark et al (2005), Reinert (1994), Borg (2009), Badinger (2013).…”